Parameter Identification Methods for an Additive Nonlinear System

Circuits, Systems, and Signal Processing - Tập 33 - Trang 3053-3064 - 2014
Jing Chen1, Yunxia Ni1
1Wuxi Professional College of Science and Technology, Wuxi , People’s Republic of China

Tóm tắt

This paper deals with parameter identification methods for an additive nonlinear system with a preload nonlinearity and a piece-wise nonlinearity. By using a switching function, we transfer the model of the additive nonlinear system into an identification model, and propose a recursive least squares algorithm and two modified stochastic gradient (SG) algorithms to estimate the parameters of the identification model. The simulation results indicate that the proposed methods converge faster than the SG algorithm.

Tài liệu tham khảo

J. Chen, F. Ding, Modified stochastic gradient algorithms with fast convergence rates. J. Vib. Control 17(9), 1281–1286 (2011)

F. Ding, System Identification—New Theory and Methods (Science Press, Beijing, 2013)

F. Ding, K.P. Deng, X.M. Liu, Decomposition based Newton iterative identification method for a Hammerstein nonlinear FIR system with ARMA noise. Circuits Syst. Signal Process. 33 (2014). doi:10.1007/s00034-014-9772-y

X.L. Luan, S.Y. Zhao, F. Liu, H-infinity control for discrete-time markov jump systems with uncertain transition probabilities. IEEE Trans. Autom. Control 58(6), 1566–1572 (2013)

E.B. Sockett, D. Daneman et al., Factors patterns of residual insulin secretion during the first year of type I diabetes mellitus in children. Diabete 30, 453–459 (1987)

B. Yu, H. Fang et al., Identification of Hammerstein output-error systems with two-segment nonlinearities: algorithm and applications. Control Intell. Syst. 38(4), 194–201 (2010)